{"product_id":"discovering-knowledge-in-data-an-introduction-to-data-mining-hardcover","title":"Discovering Knowledge in Data: An Introduction to Data Mining - Hardcover","description":"\u003cp\u003eby \u003cb\u003eDaniel T. Larose\u003c\/b\u003e (Author), \u003cb\u003eChantal D. Larose\u003c\/b\u003e (Author)\u003c\/p\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003eThe field of data mining lies at the confluence of predictive analytics, statistical analysis, and business intelligence. Due to the ever-increasing complexity and size of data sets and the wide range of applications in computer science, business, and health care, the process of discovering knowledge in data is more relevant than ever before.\u003c\/p\u003e This book provides the tools needed to thrive in today's big data world. The author demonstrates how to leverage a company's existing databases to increase profits and market share, and carefully explains the most current data science methods and techniques. The reader will \"learn data mining by doing data mining\". By adding chapters on data modelling preparation, imputation of missing data, and multivariate statistical analysis, \u003ci\u003eDiscovering Knowledge in Data, Second Edition\u003c\/i\u003e remains the eminent reference on data mining\u003cb\u003e.\u003cbr\u003e\u003cbr\u003e\u003c\/b\u003e \u003cul\u003e \u003cli\u003eThe second edition of a highly praised, successful reference on data mining, with thorough coverage of big data applications, predictive analytics, and statistical analysis.\u003c\/li\u003e \u003cli\u003eIncludes new chapters on Multivariate Statistics, Preparing to Model the Data, and Imputation of Missing Data, and an Appendix on Data Summarization and Visualization\u003c\/li\u003e \u003cli\u003eOffers extensive coverage of the R statistical programming language\u003c\/li\u003e \u003cli\u003eContains 280 end-of-chapter exercises\u003c\/li\u003e \u003cli\u003eIncludes a companion website for university instructors who adopt the book\u003c\/li\u003e \u003c\/ul\u003e\u003ch3\u003eBack Jacket\u003c\/h3\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003eThe field of data mining lies at the confluence of predictive analytics, statistical analysis, and business intelligence. Due to the ever-increasing complexity and size of data sets and the wide range of applications in computer science, business, and health care, the process of discovering knowledge in data is more relevant than ever before.\u003c\/p\u003e This book provides the tools needed to thrive in today's big data world. The author demonstrates how to leverage a company's existing databases to increase profits and market share, and carefully explains the most current data science methods and techniques. The reader will \"learn data mining by doing data mining\". By adding chapters on data modelling preparation, imputation of missing data, and multivariate statistical analysis, \u003ci\u003eDiscovering Knowledge in Data, Second Edition\u003c\/i\u003e remains the eminent reference on data mining\u003cb\u003e.\u003c\/b\u003e\u003ch3\u003eAuthor Biography\u003c\/h3\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003e\u003cb\u003eDaniel T. Larose\u003c\/b\u003e earned his PhD in Statistics at the University of Connecticut. He is Professor of Mathematical Sciences and Director of the Data Mining programs at Central Connecticut State University. His consulting clients have included Microsoft, \u003ci\u003eForbes\u003c\/i\u003e Magazine, the CIT Group, KPMG International, Computer Associates, and Deloitte, Inc. This is Larose's fourth book for Wiley.\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChantal D. Larose\u003c\/b\u003e is an Assistant Professor of Statistics \u0026amp; Data Science at Eastern Connecticut State University (ECSU). She has co-authored three books on data science and predictive analytics. She helped develop data science programs at ECSU and at SUNY New Paltz. She received her PhD in Statistics from the University of Connecticut, Storrs in 2015 (dissertation title: Model-based Clustering of Incomplete Data).\u003c\/p\u003e\u003cdiv\u003e\n\u003cstrong\u003eNumber of Pages:\u003c\/strong\u003e 336\u003c\/div\u003e\u003cdiv\u003e\n\u003cstrong\u003eDimensions:\u003c\/strong\u003e 1 x 9.3 x 6.1 IN\u003c\/div\u003e\u003cdiv\u003e\n\u003cstrong\u003eIllustrated:\u003c\/strong\u003e Yes\u003c\/div\u003e\u003cdiv\u003e\n\u003cstrong\u003ePublication Date:\u003c\/strong\u003e July 08, 2014\u003c\/div\u003e","brand":"Books by splitShops","offers":[{"title":"Default Title","offer_id":51756077678880,"sku":"9780470908747","price":143.93,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0974\/9764\/5344\/files\/cb4f2039ac7ff9920c7f01b062b33ff3.webp?v=1780073589","url":"https:\/\/ebocreations.com\/products\/discovering-knowledge-in-data-an-introduction-to-data-mining-hardcover","provider":"The E-Book Oasis LLC","version":"1.0","type":"link"}